Function get_rag_response

utils.py:191–446

(question)

def get_rag_response(question):
    try:
        # Initialize TwelveLabs client
        twelvelabs_client = TwelveLabs(api_key=TWELVELABS_API_KEY)
        
        # Generate embedding for the question with fashion context
        question_with_context = f"fashion product: {question}"
        question_embedding = twelvelabs_client.embed.create(
            model_name="Marengo-retrieval-2.7",
            text=question_with_context
        ).text_embedding.segments[0].embeddings_float
        
        search_params = {
            "metric_type": "COSINE",
            "params": {
                "nprobe": 1024,
                "ef": 64
            }
        }
        
        # Search for relevant text embeddings
        text_results = collection.search(
            data=[question_embedding],
            anns_field="vector",
            param=search_params,
            limit=2,
            expr="embedding_type == 'text'",
            output_fields=["metadata"]
        )
        
        # Search for relevant video segments
        video_results = collection.search(
            data=[question_embedding],
            anns_field="vector",
            param=search_params,
            limit=3,
            expr="embedding_type == 'video'",
            output_fields=["metadata", "vector"]  # Add vector to output fields
        )
        
        st.write(f"Retrieved {len(video_results)} video results")

        # Process text results
        text_docs = []
        for hits in text_results:
            for hit in hits:
                metadata = hit.metadata
                similarity = round((hit.score + 1) * 50, 2)
                similarity = max(0, min(100, similarity))
                
                text_docs.append({
                    "title": metadata.get('title', 'Untitled'),
                    "description": metadata.get('description', 'No description available'),
                    "product_id": metadata.get('product_id', ''),
                    "video_url": metadata.get('video_url', ''),
                    "link": metadata.get('link', '#'),  # Default to '#' if no link
                    "similarity": similarity,
                    "raw_score": hit.score,